Triple
T32493111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ochota, Warsaw |
E830443
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Warszawa Al. Jerozolimskie railway stop
Warszawa Al. Jerozolimskie railway stop is a suburban rail station in Warsaw serving the Ochota district along one of the city’s main east–west transport corridors.
|
E2008264
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Warszawa Al. Jerozolimskie railway stop | Statement: [Ochota, Warsaw, contains, Warszawa Al. Jerozolimskie railway stop]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Warszawa Al. Jerozolimskie railway stop Triple: [Ochota, Warsaw, contains, Warszawa Al. Jerozolimskie railway stop]
Generated description
Warszawa Al. Jerozolimskie railway stop is a suburban rail station in Warsaw serving the Ochota district along one of the city’s main east–west transport corridors.
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f34920aa4081908d8fb0277414b911 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c4087e048190884d3902fdc81aa5 |
completed | May 3, 2026, 3:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3466a9b1f88190bdf91016007b984c |
completed | June 18, 2026, 9:44 p.m. |
| NEDg | Description generation | batch_6a3468112b0c819084fff468a94420ad |
completed | June 18, 2026, 9:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a3468d7b1e08190ba5fa17f9e3547aa |
completed | June 18, 2026, 9:53 p.m. |
Created at: May 1, 2026, 12:59 a.m.